Adaptive environment perception in cyber-physical systems

Adaptive environment perception in cyber-physical systems
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网络物理系统中的自适应环境感知

DOI:
10.1145/2815482.2815484
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发表时间:
2015
期刊:
影响因子:
--
通讯作者:
J. Kaiser
J. Kaiser
中科院分区:
--
文献类型:
--
作者:
S. Zug;A. Dietrich;C. Steup;J. Kaiser

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相似文献

在分布式场景中自适应获取环境数据的概念带来了许多好处。如果应用程序在智能环境中聚合并使用所有可用的传感信息,则可以提供更高的精度和更高的容错性。不幸的是,与静态传感器评估相比,应用程序开发人员必须应对许多额外的挑战。在设计时为动态系统生成优化的传感器应用计划是不可能的。由于自适应选择过程,这必须在运行时执行。在本文中,我们提出了一个基于两层次分析的一般方法。第一级比较传感器参数集(周期、偏移量、延迟)和应用需求(测量次数、质量)基于最坏/最佳情况分析。如果需要更精确的评估,则需要启动第二级。这一个考虑额外的,具体情况的属性,如传感器周期的相移,通信延迟和抖动。最后,它提供了一个共同目标的在线优化,例如,最小化数据的年龄和恒定数量的输入计数。
The concept of an adaptive acquisition of environment data in distributed scenarios promises a number of benefits. If an application aggregates and uses all available sensing information in an intelligent environment it may provide a higher precision and an increased fault-tolerance. Unfortunately, the application developer has to cope with a number of additional challenges compared to static sensor evaluation. It is not possible to generate an optimized sensor application schedule for a dynamic system at design-time. Due to the adaptive selection process, this has to be executed at runtime. In this paper we propose a general approach for this problem based on a two-level analysis. The first level compares sensor parameter sets (periods, offsets, delays) and application requirements (number of measurements, quality) based on a worst/best case analysis. If a more precise evaluation is necessary, the second level needs to be started. This one considers additional, situation-specific properties like phase shift of sensor periods, communication delays and jitter. At the end, it provides an online optimization of common goals e.g., minimization of the age of data and a constant number of input counts.
无线传感器网络中的不确定性感知混合时钟同步
DOI: --
发表时间: 2014
期刊:
影响因子: --
作者:
Christoph Steup;Sebastian Zug;J. Kaiser;Andy Breuhan
通讯作者: Andy Breuhan
作为智能传感器和执行器网络的建筑控制系统的编程抽象和中间件
DOI: --
发表时间: 2010
期刊: 2010 IEEE 15th Conference on Emerging Technologies & Factory Automation (ETFA 2010)
影响因子: --
作者:
Sebastian Zug;M. Schulze;André Dietrich;J. Kaiser
通讯作者: J. Kaiser
动态组合传感器网络中控制/融合应用的相位优化
DOI: --
发表时间: 2013
期刊: International Symposium on Robotic and Sensors Environments
影响因子: --
作者:
Sebastian Zug;André Dietrich;Christoph Steup;Tino Brade;Thomas Petig
通讯作者: Thomas Petig
掌控:模块化和自适应机器人过程控制系统
DOI: --
发表时间: 2012
期刊: 2012 IEEE International Symposium on Robotic and Sensors Environments Proceedings
影响因子: --
作者:
Peter Ulbrich;Florian Franzmann;C. Harkort;Martin Hoffmann;Tobias Klaus;Anja Rebhan;Wolfgang Schröder
通讯作者: Wolfgang Schröder